Computation and simulation in delivering precision medicine

In the move to provide highly personalized healthcare and to predict individual health needs and events, High Performance Computing is becoming increasingly important to scientific discovery.

One area is in the analysis of Big Data in genomics and proteomics. Another is in computational medicine and simulation of disease progression.

When doctors look to treat a patient with a particular condition, they do so based on a number of different indicators. They will look at family history, imaging, blood tests, and increasingly they will look at genetics. In the future, predictive computational modelling may also be part of the diagnostics that will improve and personalize treatment.

This requires simulation and modelling which, in scientific terms, is still a relatively new and growing field.

What is the simulation process

In simplistic terms, biomechanical simulations (as, for example, for blood flow) is ultimately the application of Newton’s second law of motion to a problem of interest. In my work, studying cardiovascular disease, we’re trying to establish, for an individual, how and when a blood clot will form within a diseased portion of the vasculature; how you can predict when a person with a genetic mutation, which will lead to cardiovascular disease, is likely to need intervention and begin to experience health problems.

A simulation can be used to understand how the aorta deforms or stores elastic energy when blood pressure is applied. In order to simulate this, we need the following information:

Geometry – we need to understand the vascular shape and dimensions, which we can glean through medical imaging.

Applied loads – the forces applied, which we estimate through blood pressure and by applying related extra-vascular factors that can influence blood flow.

Material properties or composition – Basically this requires looking at the stiffness and strength of the aorta. When we know that a genetic mutation exists, the tissue composition and properties will be different.

Once we have these three pieces of information, we can simulate what might happen in the body over short or long periods, as, for example, when a blood clot is likely to form or when the aorta may dilate excessively. This would mean that for an individual, we would be able to predict when an intervention is likely to be needed.

How will this change healthcare delivery?

To an extent, computation and simulation already is improving healthcare. Such simulations and modelling are being used in areas such as surgical design and medical device design. They allow us to model the impact any surgical procedure or device will have on the blood flow and pressure and thus on the patient over the longer term.

Simulation is also currently helping us to understand the basic biology – both mechano- biology and immuno-biology. Increasing our understanding of how blood vessels respond to mechanical and chemical stimuli and how cells respond to their environment is critically important for understanding health and disease.

One of the most remarkable observations is the level of biological diversity across individuals. It is far greater than we would have believed. Our cells act and react very differently to the same disease stimulus or even to the same medical treatment. Even siblings with the same genetic makeup and, arguably, very similar environmental factors can react to a genetic mutation in entirely different ways – one may need intervention in their twenties and the other not until their fifties.

This biological diversity adds an enormous level of complexity to the simulation.

In some ways, as with many scientific discoveries, there are now more questions than answers. Nevertheless, medicine is and must move more towards becoming precision medicine, tailored to an individual rather than based on population averages.

Predictive simulations promise to help inform individual treatments, moving patients from emergency to elective procedures and producing better outcomes for the patient – the ultimate goal.

It’s a fascinating challenge to bring together the disciplines of medicine and engineering and together to solve problems that neither discipline could manage alone.

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About Jay D. Humphrey

Jay D. Humphrey received the Ph.D. degree in Engineering Science and Mechanics from The Georgia Institute of Technology and completed a post-doctoral fellowship in Medicine - Cardiovascular at the Johns Hopkins University, both in the USA. He is currently John C. Malone Professor and Chair of Biomedical Engineering at Yale University. He has authored three textbooks and published over 250 archival journal papers, primarily on the use of experimental and computational mechanics to understand and treat vascular disease. He served for two years as Chair of the United States National Committee of Biomechanics and is a Fellow of the American Institute of Medical and Biological Engineering and the American Society of Mechanical Engineers.

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